Monocular Visual Odometry / VIO Engineer for UAV (50–500 m, 100–300 km/h)

We are seeking a skilled Computer Vision / SLAM engineer to build a monocular Visual Odometry / Visual‑Inertial Odometry (VIO) solution for UAVs. We’ve already tried Kimera, OpenVINS, ORB‑SLAM3, and VINS‑Fusion, but results under real UAV flight conditions are not sufficient. You will develop and evaluate your solution in a simulator (large, realistic terrain, full telemetry, IMU + camera data, ground truth), then validate on real UAV flights.

Key Requirements & Constraints

Sensor Setup: Monocular camera + IMU (no stereo)

Flight Envelope:

Altitude: 50 m to 500 m

Speed: 100 km/h to 300 km/h

Real-time coordinates estimation 

On-the-fly calibration: camera intrinsics, camera‑IMU extrinsics, time sync

Feature tracking

Robust to fast maneuvers, lighting changes, and feature-sparse scenes

Clean, modular code (Java preferred, C++, Go), minimal overhead dependencies

Logging, visualization, benchmarking, test coverage

API integration for embedding into UAV stack (Raspberry Pi on Ubuntu)

What You’ll Receive / What We Provide

Simulator environment with terrain, telemetry, and ground truth

Real flight datasets for post‑simulation testing

Hardware specs (onboard / companion compute)

Support in integration, testing, and domain knowledge

Proposal Instructions

Please include in your proposal:

High-level approach/architecture (how you’d tackle VO / VIO in this envelope)

Past work or examples in SLAM / VIO / UAV

Milestones, timeline, and budget

Questions, assumptions, or clarifications needed